Health Sciences

Precision medicine across a range of diseases now equips clinicians to tailor treatment options to patients’ specific genomic and molecular profiles with the help of new technologies such as next-generation sequencing. However, developing the evidence and science to power precision medicine requires scientific exploration and validation using data that in many cases is as personal as it gets, including genomic DNA and RNA sequences that are as unique as fingerprints and difficult to make truly “anonymous.” How do we find a balance among advancing research, developing new treatments for difficult-to-treat diseases, maintaining patient privacy, and honoring patient ownership or control of sensitive data? Join experts representing policy, patient, biopharma, and other points of view moderated by Alice Crisci, CEO of MedAnswers, who is also a leader in understanding the potential commercialization issues surrounding sensitive health data and has long been a patient advocate herself.

Access to high-cost therapies presents a challenge to biopharma companies, payers, patients, and clinicians alike. What is the role of digital data in facilitating market access to these new products? From scoping market size and determining patient populations to partnering - with both payers and clinical sites—digital data from a variety of sources is becoming even more critical to decision-making. As these markets grow more complex, and more data becomes available from a growing number of sources including directly from patients in the form of Patient Reported Outcomes, the implications to risk management and mitigation, reinsurance, and strategies for both pharma and payers present questions across the ecosystem.

How will we pay for new high-cost medicines to treat diseases? Is there a way to better align incentives of biopharmaceutical manufacturers, health insurers, and health care delivery systems? “Value Based” or “Outcome Based” arrangements hold promise for aligning payments to results, but come with a host of implementation challenges ranging from pricing policy barriers to a need for high-quality data to define and measure the results, and the costs, of drugs delivered. A number of industry players are taking bold steps to test these models in the market and are learning firsthand what works, what needs improvement, and how data and outcomes can potentially power new models for drug reimbursement and pricing.

Distributed data and federated analytics models open up new avenues for health sciences researchers and health care businesses, creating options for improvement in data privacy, security, and governance as well as new opportunities for data sharing across organizations without the need for data integration. Come join us in looking at some real-world examples of distributed approaches, including recent applications related to COVID-19 testing and vaccination data, and hear expert opinions on what the most promising new areas will be for development in the field, as well as the challenges that lie ahead.

The COVID pandemic has generated billions of new data points during what may be a once-in-a-lifetime global crisis. This session explores both strategic and technical approaches to building a distributed, decentralized database that can enable research, government, and enterprise organizations to run queries and gather analytics that aid in pandemic preparedness, prevention, and management based on existing currently siloed COVID-related datasets.

A new administration is in the White House and the country is emerging from a year-long pandemic public health crisis—so, what’s currently on the table in terms of policy priorities, things to watch for, and how the Washington DC conversation will change as Biden’s first term gets underway amidst a post-pandemic recovery?

Hear from our “inside the Beltway” experts on what to expect on policy from health care to fintech, economics, and infrastructure.